Computer Science, Data Science, Data Analysis, SAS, R, SQL, Java

Akash Chawla

** ***** *****, ********* ****, Jersey City, NJ 07310

551-***-**** *****.******@*****.***

: https://www.linkedin.com/in/chawlaakash : https://github.com/akash367 Available to work: December 2016

EDUCATION

Stevens Institute of Technology, Hoboken, NJ Anticipated December 2016 Master of Science in Computer Science GPA: 4.0

Major Courses: Knowledge Discovery and Data Mining, Multivariate Data Analysis, Database Management Systems, Social Network Analysis, Web Analytics, Text Mining, Natural Language Processing Awards: Masters Fellowship Award

Guru Nanak Dev University, Amritsar, Punjab, India June 2012 Bachelor of Technology in Computer Science & Engineering GPA: 3.28 SKILLS

Programming Languages: SAS, R, Java, J2EE, SQL, JavaScript Database Systems: Oracle 9i, MS SQL Server, PostgreSQL Internet Technologies: Servlet, JSP, HTML, XML, WSDL, JSON Software: SAS 9.4, R Studio, Tableau, Eclipse, MS Office EXPERIENCE

Acquire Media, Roseland, New Jersey May 2016 – Present Data Science Intern

Develop ensemble model for Named Entity Recognition on corpus of news stories

Measure performance of different classifier algorithms Stevens Institute of Technology, Hoboken, New Jersey January 2016 – May 2016 Course Assistant, Knowledge Discovery and Data Mining

Guided students to successfully grasp complex course material Tata Consultancy Services Ltd. (TCS), Mumbai, India September 2012 – June 2015 Developer

Designed and developed frameworks and solutions as part of Centre of Excellence group

Implemented Enterprise Service Bus (ESB)/ETL framework in NatSteel Holdings Ltd

Led and trained teams in different phases of the Software Development Lifecycle

Developed a web based application in Java/J2EE integrated with Liferay Portal for EAI and B2B integrations

Developed Business Intelligence and Reporting Tool (BIRT) reports and dashboards PROJECTS

Big Mart Sales Prediction April 2016- May 2016

Implemented an ensemble of deep learning neural networks and gradient boosting regression trees in R Sentiment Analysis on Twitter Posts April 2016

Developed script in R to perform Sentiment Analysis on Twitter posts for US 2016 Presidential elections Predict the Number of Bike Rentals in an Hour October 2015- December 2015

Developed the regression model using factor analysis in SAS with 83.8% accuracy

Implemented principal component analysis and linear regression in the model Classify Whether Someone Will Face Financial Distress October 2015- December 2015

Applied various machine learning algorithms like C5.0, CART and KNN to develop a classification model

Worked in R to achieve a 93.6% accuracy in the model ACTIVITIES

President of Graduate Student Council at Stevens Institute of Technology

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